Affiliation:
1. Department of Engineering, City, University of London, London, UK
Abstract
This study assesses the predictive capability of the ZGB (Zwart-Gerber-Belamri) cavitation model with the RANS (Reynolds Averaged Navier-Stokes), the realizable k-epsilon turbulence model, and compressibility of gas/liquid models for cavitation simulation in a multi-hole fuel injector at different cavitation numbers (CN) for diesel and biodiesel fuels. The prediction results were assessed quantitatively by comparison of predicted velocity profiles with those of measured LDV (Laser Doppler Velocimetry) data. Subsequently, predictions were assessed qualitatively by visual comparison of the predicted void fraction with experimental CCD (Charged Couple Device) recorded images. Both comparisons showed that the model could predict fluid behavior in such a condition with a high level of confidence. Additionally, flow field analysis of numerical results showed the formation of vortices in the injector sac volume. The analysis showed two main types of vortex structures formed. The first kind appeared connecting two adjacent holes and is known as “hole-to-hole” connecting vortices. The second type structure appeared as double “counter-rotating” vortices emerging from the needle wall and entering the injector hole facing it. The use of RANS proved to save significant computational cost and time in predicting the cavitating flow with good accuracy.
Funder
city, university of london
Subject
Mechanical Engineering,Ocean Engineering,Aerospace Engineering,Automotive Engineering
Cited by
10 articles.
订阅此论文施引文献
订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献